The Problem

Current blockchain implementations face significant challenges in ensuring data privacy while maintaining computational efficiency. Traditional encryption methods do not allow computations on encrypted data, limiting the potential applications of blockchain in sensitive data environments. Specifically, model training typically requires plaintext data, which is a compliance issue with data protection regulations. Moreover, training complex models, such as LLMs, requires vast amounts of data that a typical consumer device will not be able to store.